Effect of longitudinal grooves of a vertical water entry cylinder on the ballistic characteristics at transitional froude numbers

ABSTRACT Random wind and wave loads on offshore structures exhibit strong coherence, which modulates their synchronous propagation and affects the combined wind-wave forces on structures. As a typical offshore foundation component, vertical circular cylinders are commonly subjected to concurrent wind and wave actions, making accurate calculation of combined loads a critical task. Based on the wind-wave coherence function, this study calculated the cross-spectrum between pulsating wind speed and incident wave elevation at the cylinder, and constructed a comprehensive wind-wave power spectral matrix covering wind auto-spectra, cross-spectra, wave spectra and wind-wave cross-spectra. A harmonic synthesis method was derived to generate random wave force time histories. Combined with Cholesky decomposition of the spectral matrix, time histories of coherent pulsating wind and wave forces were generated, and the total combined wind-wave force on the vertical cylinder was obtained by superposition.

Block copolymer self-assembly provides a promising method of generating nanoscale periodic structures with long-range order, serving as a template for advanced nano-lithographic applications. However, their intrinsic tendency towards free-energy minimization typically limits the accessible morphologies to thermodynamically preferred arrangements such as spheres on cubic lattices, hexagonally packed cylinders, or alternating lamellae. In this study, we demonstrate the formation of unconventional well-ordered square-packed arrays of vertical cylinders through one-step solvent annealing of ultrahigh molecular weight (UHMW) block copolymers (BCPs). The square-packed morphology observed in this study emerges from the interplay between low solvent vapor pressure, sluggish chain dynamics, and molecular polydispersity in UHMW BCPs, which collectively and kinetically trap the system in a metastable, nonequilibrium state favoring square symmetry. Furthermore, the introduction of a homopolymer facilitates defect healing, enhances structural stability, and enlarges the domain size by approximately 30%. These findings establish a pathway for generating square arrays as soft templates for advanced nanofabrication, offering direct compatibility with conventional integrated circuit design and fabrication.

This study examines the outcome of heat generation on thermophoretic particle deposition in Co3O4/HFE-7100 nanofluid flowing past a vertical cylinder in a permeable media under local thermal non-equilibrium conditions employing an ANN coupled with a Bayesian-regularized back-propagation algorithm. For contrast, a simplified mathematical formulation is also used to examine the thermal behavior without local thermal equilibrium assumptions, that is, without LTNE limitations. The solid matrix and fluid phase are treated as distinct temperature fields in the LTNE framework, necessitating unique thermal gradients for each phase. Optimizing heat transfer performance using ANN-based regression modeling is the main goal of this work. Well-structured training and testing datasets are used to guarantee numerical stability and prediction resilience, and the Bayesian-regularization back-propagation technique is applied to enhance generalization capacity. The impact of dominating governing factors is illustrated graphically, and an error evaluation is provided to gauge model correctness. The ANN model was trained using the obtained dataset and then tested against numerical values of important engineering variables. Tables and graphs are utilized to show how new factors affect the flow’s dynamics. The rate of liquid phase heat transmission declines as the inter-phase heat transport values increase.

For a thin liquid film around a vertical solid cylinder, this study aims to understand the flow phenomenon while it falls down the cylinder assisted by gravity, using a three-dimensional finite volume scheme. The problem is described broadly in three stages of development, i.e., film dynamics, convergence of film into a jet, and jet behavior. The interplay between inertia, gravity, and surface tension dictates these evolutions: gravity promotes vertical drainage, inertia stabilizes the jet, and surface tension minimizes the interface area, leading to Rayleigh–Plateau instability, which ultimately produces droplet breakup. The film flow is described with a self-similar scaling. Pressure distributions and velocity vectors are employed to understand convergence. Correlations are developed for the dripping/jet responses to the globally defined parameters. The jet formation is represented as a direct consequence of the propagation of wave patterns on the film, highlighting that the spatial and temporal evolution of film disturbances sets the parameters for the jet's velocity profile, diameter, and breakup phenomenon, summarized in a parametric regime map. Finally, a Lagrangian analogy is constructed between interwoven beads falling down a vertical pole and the draining liquid moieties, where the attractive inter-bead forces, mimicking surface tension, overcome the inertial resistance to effectively pinch the layer to capillary length scale.

Breaking wave-induced slamming loads on vertical cylinders from underlying linear wave properties and parametric models

Ice response to a pulsating point source near a vertical cylinder

Objective: The Bridgman–Stockbarger method is a critical technique for producing high-purity single crystals, with significant applications in semiconductor and photovoltaic industries. This study explores the enhancement of thermal performance in coaxial cylindrical furnaces—common in crystal growth systems—through the use of nanofluids. Methods: A Multi-Relaxation-Time lattice Boltzmann method (MRT-LBM) is employed to simulate natural convection and heat transfer within the annular space between vertical cylinders. The model incorporates radial coordinates into the temperature distribution, simplifying the source term requirement. Validation via Chapman–Enskog analysis confirms the recovery of the macroscopic energy equation. Results: Results include detailed distributions of temperature, velocity streamlines, and entropy generation, highlighting improvements in heat transfer efficiency and thermodynamic performance. Conclusion: This research underscores the potential of nanofluid-based thermal management to support energy-efficient material processing, with direct implications for the development of advanced materials, including high-performance ceramics, composites, and sustainable construction technologies.

Purpose In this study a numerical investigation of the heat transfer within a vertical conical porous cylinder has considered epistemic type uncertainties and accordingly, the problem is modelled. Because in this problem the uncertainties may arise due to defined boundary conditions, insufficient information about the system, experimental errors etc. Design/methodology/approach The study aims to handle uncertain involved systems. The uncertain involved coupled momentum and energy equations are solved through the proposed fuzzy finite element method (FFEM). The converted coupled algebraic equations are resolved through the Gauss–Seidel iterative approach. Also, the uncertain parametric effect is investigated for finding the stability of the system. Findings A case study is presented to demonstrate the utility and efficiency of the proposed method. The effects of Ra and Rd on the stream function and temperature distribution are analysed for different Alpha-cut values. Furthermore, the sensitivity of the imprecise parameters involved is examined. The results indicate that both Ra and Rd are the most influential parameters in determining the temperature and stream function of the system when only two parameters are considered uncertain. Practical implications The proposed method can be included in different practical application problems to analyse the parametric effects like geothermal analysis, nuclear reactor system and different porous structured problems. Originality/value The novelty of the system is the implementation of the proposed method like FFEM and Gauss–Seidel method in the conical porous cylinder. Also, the sensitivity of the uncertain parametric effect is analysed to study the stability of the system. This kind of structure is found in real-life applications like gas thermal analysis, geothermal analysis etc.

A case study of natural convection heat transfer from circular fin arrays on a vertical cylinder

Numerical investigation of the secondary load cycle and high-frequency response on a vertical cylinder under focused waves

The structure of gravity currents flowing around a wall-mounted vertical circular cylinder

ABSTRACT In this work, the unsteady heat and mass transport properties of a Casson fluid passing over an oscillating vertical cylinder embedded in a Darcy–Forchheimer porous medium are examined. The growing industrial application of oscillatory cylindrical systems in drilling operations, increased oil recovery, biochemical reactors, and polymer processing, where non‐Newtonian fluids interact with porous materials under periodic motion is the motivation behind this work. In order to effectively represent transport phenomena found in petroleum reservoirs, chemical mixing towers, food processing facilities, and heat exchange devices, this model integrates Soret and Dufour effects, viscous dissipation, chemical reaction, and heat generation/absorption. A dimensional partial differential system of equations is created by formulating the governing equations of momentum, energy, and concentration. The suitable transformations are then applied in the governing model to obtain the dimensionless form in terms of partial differential equations. To solve the equations numerically, a reliable and effective Crank‐Nicolson finite difference technique is implemented. The understanding of how to regulate heat and mass flow in porous geometries is made easier by this work. The effects of significant parameters on velocity, temperature, and concentration are investigated numerically and graphically.

This work investigates how a vertical cylindrical obstacle affects the dynamics and mixing of lock-release gravity currents. Gravity currents are produced in the laboratory and density fields are measured using an image analysis. Two Reynolds numbers, three submergence ratios and three flow blockage ratios have been tested. Results show that upstream of the cylinder, gravity currents propagation remains unaffected. Downstream of the obstacle, the front velocity decreases compared to the undisturbed case, with a deceleration becoming larger as the obstacle diameter increases. The deceleration does not trigger the transition from the slumping to the self-similar phase. Greater obstacle height causes an increased current thickness upstream of the cylinder, while larger diameters amplify both the thickness and the reflection of the dense current. The entrainment parameter remains unchanged across all tested configurations. Energy budget analysis reveals an enhancement of mixing in the presence of obstacles.

Optimisation offers a clear way to determine the best parameter settings for a desired output. Combined with sensitivity analysis, it helps identify both the optimal conditions and the variables that influence the response the most. Hence, this study focuses on the heat transfer optimisation and sensitivity analysis of a ternary nanofluid (Al2O3 – TiO2 – Cu/H2O) flow over a shrinking vertical cylinder with magnetohydrodynamics (MHD), radiation, heat absorption/generation, and velocity slip, which delivers its novelty in the optimisation approach. The governing equations are formed through similarity transformation and solved numerically using the bvp4c solver in MATLAB. The results show a bifurcation in the flow, giving rise to upper and lower solution branches. The ternary nanoparticles also give a clear rise in the heat transfer rate. Response Surface Methodology (RSM) is then used in Minitab to optimise four selected parameters. The highest heat transfer rate of 56.103% occurs when the magnetic field, heat generation, and Cu-nanoparticle fraction are at their highest levels, while radiation is at its lowest. Sensitivity analysis shows that heat generation has the strongest effect on heat transfer. This combined RSM and sensitivity approach offers a practical way to improve heat transfer in ternary nanofluid systems and supports SDG7. Highlights This research deals with a ternary nanofluid Al2O3-TiO2-Cu/H2O flow over a shrinking vertical cylinder with velocity slip, MHD, radiation, and heat absorption/generation. PDEs are transformed into a system of ODEs, which further solved using the bvp4c program code in MATLAB. RSM optimisation is employed in Minitab and shows that the maximum rate of 56.103% is achieved with optimal parameter settings. Sensitivity analysis ranks the influence of parameters: heat generation, Cu-nanoparticles, radiation, and magnetic field.

In this paper, We show using Laplace and finite Hankel transforms, how to derive exact solutions for the velocity and temperature profiles of a system of fractional differential equations which describe heat transfer by natural convection of a specific engine oil with molybdenum disulphide and graphene oxide (MoS2 + GO) hybrid nano-composites in oscillating vertical cylinder. A few figures are used to illustrate how the temperature profile and the Nusselt number are affected by the Prandtl number and the order of the fractional derivative.

The efficient storage of liquid hydrogen is challenged by heat inleak, which leads to evaporation, self-pressurization and potential venting losses. To analyze these processes, a lumped-parameter modeling approach is employed, accounting for non-equilibrium effects between the liquid and vapor phases, while capturing the essential physics. A particular challenge arises from the prediction of heat transfer across the phase boundary, as commonly available Nusselt number correlations do not directly reproduce the observed behavior for cryogenic hydrogen. This issue is addressed by introducing a single fitting parameter for each relevant tank geometry, namely vertical cylinder, horizontal cylinder, and sphere, with the values determined by fitting to experimental data. The resulting maximum deviations between simulation and experiment are within approximately 10 % for the vertical and horizontal cylinders and 15 % for the sphere, which confirms the capability of the model to capture the relevant pressurization dynamics. Overall, the proposed approach provides a computationally efficient and thermodynamically consistent tool for analyzing the self-pressurization and boil-off characteristics of liquid hydrogen storage systems across all relevant tank geometries. • Model reliably predicts pressure in LH2 tanks for all relevant geometries. • The developed lumped-parameter model requires only one single fitting parameter. • Efficient, thermodynamically consistent tool to model self-pressurization. • Simulation results show good agreement with experimental measurements.

Heat transfer in thin film flow of carbon nanotubes over a vertical cylinder: A Bayesian regularization neural network approach

Physics-informed neural network approach to unsteady fractional flow in a vertical coaxial annulus with thermal effects and magneto-hall interaction

A computational investigation is carried out for Carreau-type non-Newtonian flows past a vertically aligned cylinder. The rheological behavior of the Carreau fluid is captured through a set of boundary layer equations incorporating buoyancy, magnetic field effects, viscous dissipation and stretching. For accuracy and reliability, the resulting problem is solved using two independent numerical approaches: the shooting method coupled with a fifth-order Runge–Kutta scheme and Newton's method, as well as MATLAB's built-in boundary value solver. Flow and thermal characteristics are modeled using an artificial neural network trained with the Levenberg–Marquardt (LM) algorithm. The reliability of the predictions is verified through multiple validation metrics, and a comparison between the bvp4c scheme and the artificial neural network model reveals remarkable agreement. Results reveal how shear-thinning characteristics and magnetic field intensity jointly influence the momentum and thermal boundary layers. Graphical illustrations provide further insight into the evolving structure of the flow and temperature fields under various operating conditions. With an increasing curvature parameter and thicker momentum, thermal and concentration boundary layers are formed. By increasing the parameter k * , the thermophoretic diffusion mechanism strengthens leading to a higher thermophoretic velocity. The impact of key physical parameters—including the power-law index, Weissenberg number, magnetic interaction parameter and Eckert number—on the wall shear stress and heat transfer rate is systematically explored.